Reflection of public debt in financing deficit, capital investments and economic growth in Kosovo and level comparison with other countries
Bibliographic record
Abstract
In this paper, we present the processes of public debt development in Kosovo for the period of its functioning, respectively from 2009 until 2018. There is no long history of it, but there is a dynamic constant growth. The methodology used in this paper is based on empirical study analysis, and the scientific literature we have elaborated has found that many thinkers who support public debt with arguments justify this non-fiscal instrument to finance the budget deficit as well as some others who object it. In addition to the international debt with 42% share, in 2012, the domestic debt began to function, with securities issuing at 58%. Along with the country's economic growth, we have also increased budget, and GDP growth. While every year we have an average economic growth of 3.2% to 3.5%. In 2013, compared to 2012, the budget increase is 1.96%, in 2016 compared to 2015 is 7%. In 2017 compared to 2016 we have a growth of 8.31%. In 2009, the debt-to-GDP ratio had a share of 6.12%, in 2014 it reached 10.65%, in 2017 the share of debt to GDP (GDP) was 16.63% and in Q3 of 2018 it was 16.92 %. In the countries of the region and the European Union we have different levels. Most states have a high level of debt to GDP.The study of the literature review was carried out using selected four databases containing publications. Research has been done to find out how much the public debt level is based on the specifics of the economy and fiscal policy in Kosovo. In addition to the dynamics of public finance development, public debt has also been realized.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.011 | 0.012 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".